Image Processing and Statistical Analysis as an Aid in the Comparison of Typewritten Impressions

1987 ◽  
Vol 32 (4) ◽  
pp. 12407J ◽  
Author(s):  
Michael G. Noblett
Keyword(s):  
Image Processing ◽  
Statistical Analysis

Detection of Leukemia Using Image Processing

2018 ◽  
Vol 8 (4) ◽  
pp. 61
Author(s):  
A. Sivasangari ◽  
G. Sasikumar
Keyword(s):  
Image Processing ◽  
Statistical Analysis ◽  
Early Detection ◽  
Visual Inspection ◽  
Causes Of Death ◽  
Cure Rate ◽  
Blood Disorders ◽  
Detection And Diagnosis ◽  
The Moment ◽  
Early Detection And Diagnosis

Leukemia   disease   is one   of    the   leading   causes   of death   among   human. Its  cure  rate and  prognosis   depends   mainly   on  the  early  detection   and  diagnosis  of   the  disease. At  the  moment, identification  of  blood  disorders  is  through   visual  inspection  of  microscopic  images  by  examining  changes  like  texture, geometry, colour  and   statistical  analysis  of  images . This  project  aims  to  preliminary  of  developing  a  detection  of  leukemia  types  using   microscopic  blood  sample using MATLAB. Images  are  used  as  they  are  cheap  and  do  not  expensive  for testing  and  lab  equipment.

Experimental investigation of single bubbles rising in stagnant liquid: Statistical analysis and image processing

2021 ◽  
Vol 33 (10) ◽  
pp. 103611
Author(s):  
Ida K. Kure ◽  
Hugo A. Jakobsen ◽  
Nicolas La Forgia ◽  
Jannike Solsvik
Keyword(s):  
Image Processing ◽  
Experimental Investigation ◽  
Statistical Analysis

A new methodology for detection of counterfeit Viagra® and Cialis® tablets by image processing and statistical analysis

2012 ◽  
Vol 216 (1-3) ◽  
pp. 92-96 ◽  
Author(s):  
Claudio R. Jung ◽  
Rafael S. Ortiz ◽  
Renata Limberger ◽  
Paulo Mayorga
Keyword(s):  
Image Processing ◽  
Statistical Analysis

Image processing and statistical analysis of microstructures of as plasma sprayed Alumina–13 wt.% Titania coatings

2006 ◽  
Vol 201 (6) ◽  
pp. 3691-3700 ◽  
Author(s):  
R. Venkataraman ◽  
Gautam Das ◽  
B. Venkataraman ◽  
G.V. Narashima Rao ◽  
R. Krishnamurthy
Keyword(s):  
Image Processing ◽  
Statistical Analysis ◽  
Plasma Sprayed ◽  
Titania Coatings

Quantification and Statistical Analysis of Microstructural Features in As-Cast Ti-6Al-4V Titanium Alloy

2013 ◽  
Vol 747-748 ◽  
pp. 828-832
Author(s):  
Xiang Jun Cheng ◽  
Guo Qing Wu ◽  
Jia Qi Zhao
Keyword(s):  
Image Processing ◽  
Grain Size ◽  
Titanium Alloy ◽  
Statistical Analysis ◽  
Normal Distribution ◽  
Plate Thickness ◽  
Two Phase ◽  
The Relationship ◽  
Α Lamella ◽  
Cast Plate

Based on microstructure of as-cast Ti-6Al-4V titanium alloy, an image processing to simplify model of β grain size, α lamella space was developed and a quantitative statistical method of β grain size, α lamella space in two-phase titanium alloys was established, with which β grain size and α lamella space of as-cast Ti-6Al-4V titanium alloy with different plate thickness were analyzed. The relationship between β grain size, α lamellar space and cast plate thickness was discussed. The results show that β grain size and α lamellae thickness nearly linearly increase as plate thickness increasing. β grain size has normal distribution and with cast plate thickness increasing, the dispersion gets larger.

scholarly journals Image processing based method for characterization of the fat/meat ratio and fat distribution of pork and beef samples

2013 ◽  
Vol 9 (1) ◽  
pp. 27-53
Author(s):  
J. Felfoldi ◽  
L. Baranyai ◽  
F. Firtha ◽  
L. Friedrich ◽  
Cs. Balla
Keyword(s):  
Image Processing ◽  
Statistical Analysis ◽  
Fat Distribution ◽  
Quality Characteristics ◽  
Raw Material ◽  
Important Quality ◽  
Textural Parameters ◽  
Rgb Images ◽  
Classification Function

The fat content (fat distribution) of the pork and beef raw material is one of their most important quality characteristics. Image processing methods were applied to provide with quantitative parameters related to these properties. Different hardware tools were tested to select the appropriate imaging alternative. Statistical analysis of the RGB data was performed in order to find appropriate classification function for segmentation. Discriminant analysis of the RGB data of selected image regions (fat-meat-background) resulted in a good segmentation of the fat regions. Classification function was applied on the RGB images of the samples, to identify and measure the regions in question. The fat-meat ratio and textural parameters (entropy, contrast, etc.) were determined. Comparison of the image parameters with the sensory evaluation results showed an encouraging correlation.

scholarly journals Morphological and statistical analysis of biomaterials with applications in tissue engineering by means of microscopy image processing

2011 ◽  
Vol 9 (3) ◽  
pp. 399-407
Author(s):  
Ramon Cardona Marsal ◽  
Manuel Salmeron Sanchez ◽  
Ana Valles Lluch ◽  
David Moratal
Keyword(s):  
Image Processing ◽  
Tissue Engineering ◽  
Statistical Analysis ◽  
Microscopy Image
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